Method and system for processing a multi-channel image

ABSTRACT

A method for processing a multi-channel image includes modification of adjusted pixel values of one or more pixels in a region of the multi-channel image, in accordance with a pre-specified signal pattern based on one or more parameters. A score is determined based on a ratio of a pixel difference value and a maximum pixel step value. The maximum pixel step value corresponds to modified pixel values of the one or more pixels in the region when the maximum pixel step value exceeds a threshold noise level for the region. False color is suppressed in a selected region of the multi-channel image based on the determined score when the false color is identified in the region.

REFERENCE

None.

FIELD

Various embodiments of the disclosure relate to processing amulti-channel image. More specifically, various embodiments of thedisclosure relate to processing a multi-channel image for suppression ofaliased colors.

BACKGROUND

The integration of camera systems into devices has created a largevariety of systems of different shapes, sizes, and functionalities.These devices, for example, include smart phones, surveillance cameras,wearable cameras, camcorders, digital single-lens reflex cameras,mirror-less cameras, and tablets. The integration of the camera systemsmay require a tradeoff in image quality, device size, and/or costs.Usually, a desire for improved image quality remains same although thesystems and image/video capturing platforms may change. For example,digital images and video frames may have certain issues with imagequality related to sharpness, noise, distortions, artifacts, and/orchromatic aberration.

In image processing and photography, aliasing is an effect that causesdifferent signals to become indistinguishable or aliases of one anotherwhen sampled. A digital image sampling system may suffer from aliasingwhen the input signal's frequency is higher than the Nyquist frequencyof the system. For a digital image, distortions and artifacts mayresult, when the digital image may be reconstructed from samplesdifferent from the original scene. For multi-channel images, such asdigital color images, reconstructed by colored image sampling systems,colors that may be different from those in the actual scenes may appearin some regions of reconstructed color images due to aliasing. Suchfalse colors may be more noticeable to a human visual system, andusually referred to as “color aliasing”.

Typically, a multi-channel image is obtained via a single image sensoroverlaid with a spatial color filter array (CFA), which is a mosaic oftiny color filters placed over each pixel. The most famous CFA patternis the Bayer pattern that involves red, green, and blue filters. Imagingsensors equipped with the Bayer CFA pattern are often called Bayersensors. Imaging sensors equipped with a CFA tend to suffer from coloraliasing from processing. In order to suppress color aliasing, filterssuch as optical anti-aliasing filters are generally applied in front ofa color-imaging sensor. However, these filters result in a tradeoff inpicture quality as the filters reduce the overall sharpness of acaptured image.

In order to increase the sharpness of captured images and reduceproduction cost, more and more image sensors are manufactured withoutoptical anti-aliasing filters. Thus, a need still remains for an imageprocessing system that can deliver sharpness in picture quality whilestill removing and suppressing the disadvantages of color aliasing. Inview of the increasing demand for providing higher resolution images andvideos, it is increasingly critical that answers or solutions need befound to these problems.

The aliased colors in the one or more regions of the multi-channel imagemay be present in different patterns, such as a circular pattern, cornercircular pattern, and/or moiré pattern, based on a change in pixelvalues in a color-aliased region. Thus, there is a need for an efficientand a robust anti-aliasing technique and/or system that may suppress thealiased colors, which are in specific signal patterns, in one or morecolor-aliased regions in the multi-channel image.

Further limitations and disadvantages of conventional and traditionalapproaches will become apparent to one of skill in the art, throughcomparison of described systems with some aspects of the presentdisclosure, as set forth in the remainder of the present application andwith reference to the drawings.

SUMMARY

A method and a system to process a multi-channel image are providedsubstantially as shown in, and/or described in connection with, at leastone of the figures, as set forth more completely in the claims.

These and other features and advantages of the present disclosure may beappreciated from a review of the following detailed description of thepresent disclosure, along with the accompanying figures in which likereference numerals refer to like parts throughout.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram that illustrates various components of animage-processing device utilized to process a multi-channel image, inaccordance with an embodiment of the disclosure.

FIG. 2A illustrates a first arrangement of various components of animage-processing device, to determine a score that corresponds to anidentification of a pre-specified signal pattern in adjusted pixelvalues of one or more pixels in a multi-channel image region, inaccordance with an embodiment of the disclosure.

FIG. 2B illustrates a method for computation of a pixel step value and apixel offset value for a multi-channel image region, in accordance withan embodiment of the disclosure.

FIG. 2C illustrates an exemplary scenario that represents acorrespondence between a modified region and a mathematicalrepresentation model of a three-dimensional (3D) pyramid, in accordancewith an embodiment of the disclosure.

FIG. 2D illustrates an exemplary scenario that represents a 3D pyramidmodel for modified region, in accordance with an embodiment of thedisclosure.

FIG. 2E illustrates an exemplary scenario that represents determinationof a pixel difference value between adjusted pixel values and modifiedpixel values of one or more pixels of a multi-channel image region, inaccordance with an embodiment of the disclosure.

FIG. 3 illustrates a second arrangement of various components of animage-processing device, to depict a method and system for suppressionof color-aliased region of a demosaiced multi-channel image region of amulti-channel video frame, in accordance with an embodiment of thedisclosure.

FIG. 4 illustrates a flow chart for implementation of an exemplarymethod for processing a multi-channel image, in accordance with anembodiment of the disclosure.

DETAILED DESCRIPTION

Various implementations may be found in a method and/or a system toprocess a multi-channel image. The following embodiments are describedin sufficient detail to enable those skilled in the art to make and usethe disclosed embodiments. While the present disclosure has beendescribed with reference to certain embodiments, it will be understoodby those skilled in the art that various changes may be made andequivalents may be substituted without departing from the scope of thepresent disclosure

In the following description, numerous specific details are given toprovide a thorough understanding of the disclosure. However, it may beapparent that the disclosed embodiments may be practiced without thesespecific details. In order to avoid obscuring the present disclosure,some well-known definitions, circuits, system configurations, andprocess steps are not disclosed in detail.

The drawings showing embodiments of the system are semi-diagrammatic andnot to scale and, particularly, some of the dimensions are for theclarity of presentation and are shown exaggerated in the drawings. Wheremultiple embodiments are disclosed and described having some features incommon, for clarity and ease of illustration, description, andcomprehension thereof, similar and like features one to another willordinarily be described with similar reference numerals.

FIG. 1 is a block diagram that illustrates various components of animage-processing device utilized to process a multi-channel image, inaccordance with an embodiment of the disclosure. With reference to FIG.1, there is shown an image-processing device 100. The image-processingdevice 100 may comprise one or more processors, such as a processor 102,a memory 104, a transceiver 106, a color adjustment unit 108, a colormodification unit 110, a Pixel Difference Determination (PDD) unit 112,a noise compensation unit 114, and a scoring unit 116. Theimage-processing device 100 may further comprise a demosaic unit 118, aFalse Color Suppression (FCS) unit 120, one or more input/output (I/O)devices, such as an I/O device 122, a data acquisition unit 124, and asecondary storage unit 126.

The processor 102 may comprise suitable logic, circuitry, interfaces,and/or code that may be configured to execute a set of instructionsstored in the memory 104 and/or the secondary storage unit 126. Theprocessor 102, in conjunction with the color adjustment unit 108, thecolor modification unit 110, the PDD unit 112, the noise compensationunit 114, and/or the scoring unit 116, may be operable to process one ormore multi-channel images. The processing may correspond to suppressionof color-aliasing in multi-channel image regions of the one or moremulti-channel images. The processor 102 may be implemented based on anumber of processor technologies known in the art. Examples of theprocessor 102 may be an X86-based processor, a Reduced Instruction SetComputing (RISC) processor, an Application-Specific Integrated Circuit(ASIC) processor, a Complex Instruction Set Computing (CISC) processor,and/or other processors.

The memory 104 may comprise suitable logic, circuitry, and/or interfacesthat may be configured to store a machine code and/or a computer programwith at least one code section executable by the processor 102. Examplesof implementation of the memory 104 may include, but are not limited to,Random Access Memory (RAM), Dynamic Random Access Memory (DRAM), StaticRandom Access Memory (SRAM), Thyristor Random Access Memory (T-RAM),Zero-Capacitor Random Access Memory (Z-RAM), Read Only Memory (ROM),and/or cache memory.

The transceiver 106 may comprise suitable logic, circuitry, interfaces,and/or code that may be configured to communicate with a user terminal(not shown), via a communication network (not shown). The transceiver106 may implement known technologies to support wired or wirelesscommunication of an external source (not shown) with the communicationnetwork. Various components of the transceiver 106 may include, but arenot limited to, an antenna, a radio frequency (RF) transceiver, one ormore amplifiers, a tuner, one or more oscillators, a digital signalprocessor, a coder-decoder (CODEC) chipset, a subscriber identity module(SIM) card, and/or a local buffer.

The transceiver 106 may communicate with networks, such as the Internet,an Intranet and/or a wireless network, such as a cellular telephonenetwork, a wireless local area network (LAN), and/or a metropolitan areanetwork (MAN), via wireless communication. The wireless communicationmay use any of a plurality of communication standards, protocols andtechnologies, such as Global System for Mobile Communications (GSM),Enhanced Data GSM Environment (EDGE), wideband code division multipleaccess (W-CDMA), code division multiple access (CDMA), time divisionmultiple access (TDMA), Bluetooth, Wireless Fidelity (Wi-Fi) (such asIEEE 802.11a, IEEE 802.11b, IEEE 802.11g, and/or IEEE 802.11n), voiceover Internet Protocol (VoIP), Wi-MAX, a protocol for email, instantmessaging, and/or Short Message Service (SMS).

The color adjustment unit 108 may comprise suitable logic, circuitry,interfaces, and/or code that may be configured to adjust pixel values ofone or more pixels in a multi-channel image region. The color adjustmentunit 108 may be further configured to convert the multi-channel imageinto a mono-channel image. The color adjustment unit 108 may beimplemented based on a number of processor technologies known in theart.

The color modification unit 110 may comprise suitable logic, circuitry,interfaces, and/or code that may be configured to modify the adjustedpixel values of one or more pixels in the multi-channel image region,which is in accordance with a pre-specified signal pattern, of themulti-channel image. The modification may be based on one or moreparameters, such as a pixel offset value and a pixel step value, inaccordance with a pre-specified signal pattern (such as a pyramidpattern). The color modification unit 110 may be implemented based on anumber of processor technologies known in the art.

The PDD unit 112 may comprise suitable logic, circuitry, interfaces,and/or code that may be configured to determine a pixel difference valuebetween the adjusted pixel values and the modified pixel values of theone or more pixels in the multi-channel image region. The PDD unit 112,in conjunction with the processor 102, may determine the pixeldifference value, based on various mathematical functions. Examples ofthe mathematical functions that may include, but are not limited to, asum of absolute difference (SAD) function, a sum of squared difference(SSD) function, a weighted sum of absolute difference (WSAD) functionand/or a weighted sum of squared difference (WSSD) function.Notwithstanding, other mathematical functions known in the art may alsobe implemented, without deviation from the scope of the disclosure. ThePDD unit 112 may be implemented based on a number of processortechnologies known in the art.

The noise compensation unit 114 may comprise suitable logic, circuitry,interfaces, and/or code that may be configured to determine a thresholdnoise level of the adjusted pixel values of one or more pixels in themulti-channel image region. The noise compensation unit 114 may befurther configured to perform noise compensation on the adjusted pixelvalues to compensate various types of noise signals associated with theadjusted pixel values. The noise compensation may be performed based onone or more noise compensation algorithms, such as a linear filteringalgorithm, a median filtering algorithm, and/or an adaptive filteringalgorithm. Examples of the various types of noise signals may include,but are not limited to, an additive white Gaussian noise, aSalt-and-pepper noise, a Shot noise, a Quantization noise (uniformnoise), a Film grain noise, and/or an Anisotropic noise. The noisecompensation unit 114 may be implemented based on a number of processortechnologies known in the art.

The scoring unit 116 may comprise suitable logic, circuitry, interfaces,and/or code that may be configured to determine a score, based on aratio of a pixel difference value and a maximum pixel step value. Themaximum pixel step value may correspond to a maximum pixel value fromthe modified pixel values of the one or more pixels in the multi-channelimage region. The scoring unit 116 may be implemented based on a numberof processor technologies known in the art.

The demosaic unit 118 may comprise suitable logic, circuitry,interfaces, and/or code that may be configured to perform interpolationto recover a full set of color channels from a CFA sub-sampledmulti-channel image. The demosaic unit 118 may perform suchinterpolation, based on various demosaic algorithms known in the art,such as a simple interpolation algorithm, a pixel correlation within themulti-channel image, and/or video super-resolution algorithm. Thedemosaic unit 118 may be implemented, based on a number of processortechnologies known in the art.

The FCS unit 120 may comprise suitable logic, circuitry, interfaces,and/or code that may be configured to suppress color aliasing (or falsecolor) present in the full set of color channels of the multi-channelimage recovered by the demosaic unit 118. The FCS unit 120 may befurther configured to perform operations, such as alpha blending, todigitally suppress false color present in the multi-channel image. TheFCS unit 120 may be implemented based on a number of processortechnologies known in the art.

The I/O device 122 may comprise suitable logic, circuitry, interfaces,and/or code that may be configured to receive an input from the user.The input from the user may correspond to an image capture of a scene.The I/O device 122 may be further configured to provide an output to theuser. The I/O device 122 may comprise various input and output devicesthat may be configured to communicate with the processor 102. Examplesof the input devices may include, but are not limited to, a touchscreen, a keyboard, a mouse, a joystick, a microphone, a motion sensor,a light sensor, and/or a docking station. Examples of the output devicesmay include, but are not limited to, a display screen, a projectorscreen, and/or a speaker.

The data acquisition unit 124 may comprise suitable logic, circuitry,interfaces, and/or code that may be configured to capture themulti-channel image. The data acquisition unit 124 may comprise one ormore imaging sensors to capture the multi-channel image. Examples of theone or more imaging sensors in the data acquisition unit 124 mayinclude, but are not limited to, a semiconductor charged couple device(CCD), an active pixel sensors in complementarymetal-oxide-semiconductor (CMOS), an N-type metal-oxide-semiconductor(NMOS), a Live MOS, and/or a flat panel detector.

The secondary storage unit 126 may comprise suitable logic, circuitry,interfaces, and/or code that may be configured to store themulti-channel image. The secondary storage unit 126 may receive themulti-channel image from the data acquisition unit 124, the remote dataacquisition unit (not shown), or other such imaging devices. Inaccordance with an embodiment, the secondary storage unit 126 may befurther configured to store a pixel step value and a pixel offset value,computed by the color modification unit 110, in conjunction with theprocessor 102. In accordance with an embodiment, the secondary storageunit 126 may be further configured to store a pixel difference value,computed by the PDD unit 112. In accordance with an embodiment, thesecondary storage unit 126 may be further configured to store athreshold noise level, determined by the noise compensation unit 114. Inaccordance with an embodiment, the secondary storage unit 126 may befurther configured to store a score, determined by the scoring unit 116.In accordance with an embodiment, the secondary storage unit 126 maycomprise a non-volatile semiconductor memory in which one or more blockareas that constitute the non-volatile semiconductor memory may be usedto store the multi-channel image. Examples of the secondary storage unit126 may include, but not limited to, a Hard disk drive (HDD), a storageserver, a Secure Digital (SD) card, and a flash memory.

In operation, the processor 102 may generate a request for amulti-channel image and communicate the request to the transceiver 106.The request may be generated based on an input provided by a user, viathe I/O device 122. The input from the user may correspond to an imagecapture of a scene, such as a soccer match. The transceiver 106 maytransmit the request to an external source, such as a server (notshown), via a communication network. Based on the transmitted request,the transceiver 106 may receive the multi-channel image from theexternal source, via the communication network. In a particularinstance, the external source may be associated with a televisionbroadcasting station. In another instance, the external source may beimplemented as a single server, a cluster of servers, or a cloud server.The implementation of the external source may be based on severaltechnologies that are well known to those skilled in the art.

The communication network may include a medium through which theprocessor 102 may communicate with the external source, via thetransceiver 106. Examples of the communication network may include, butare not limited to, the Internet, a Dedicated Short-Range Communication(DSRC) network, a Mobile Ad Hoc Network (MANET), an Internet-basedMobile Ad Hoc Network (IMANET), a Wireless Sensor Network (WSN), aWireless Mesh Network (WMN), the Internet, a cellular network, aLong-Term Evolution (LTE) network, a cloud network, a Wireless Fidelity(Wi-Fi) network, a Wireless Local Area Network (WLAN), a Local AreaNetwork (LAN), a plain old telephone service (POTS), and/or aMetropolitan Area Network (MAN). Various devices in the networkenvironment (not shown) may be configured to connect to thecommunication network, in accordance with various wired and wirelesscommunication protocols. Examples of such wired and wirelesscommunication protocols may include, but are not limited to, IEEE802.11, 802.11p, 802.15, 802.16, 1609, Worldwide Interoperability forMicrowave Access (Wi-MAX), Wireless Access in Vehicular Environments(WAVE), cellular communication protocols, Transmission Control Protocoland Internet Protocol (TCP/IP), User Datagram Protocol (UDP), HypertextTransfer Protocol (HTTP), Long-term evolution (LTE), File TransferProtocol (FTP), ZigBee, Enhanced Data rates for GSM Evolution (EDGE),infrared (IR), and/or Bluetooth (BT) communication protocols.

In accordance with an embodiment, the processor 102 may be configured toreceive the multi-channel image directly from the image sensors of thedata acquisition unit 124. In accordance with an embodiment, theprocessor 102 may be configured to receive the multi-channel image froma remote data acquisition unit (not shown), via the communicationnetwork. In such a case, the remote data acquisition unit may becommunicatively connected to the image-processing device 100. Theprocessor 102 may be further configured to store the multi-channel imagein the secondary storage unit 126.

In accordance with an embodiment, the processor 102 may be configured toretrieve the multi-channel image from the secondary storage unit 126.The one or more channels of the multi-channel image may be utilized tospecify the color of each pixel, in accordance with the color model ofthe multi-channel image. For example, an RGB image has three channels:one for Red, one for Green and one for Blue. In another example, a CMYKimage has four channels: one for Cyan, one for Magenta, one for Yellow,and one for Black. Examples of the multi-channel image may include, butare not limited to, a digital color photograph, a digital color video, aBayer sensor raw image, and/or a multi spectral image (that may comprisemultiple channels/frequency components). The multi-channel image maycontain data of a certain color space, such as RGB (OfficialSpecification “IEC 61966-2-1:1999”) or YUV (Official Specification“ITU-R BT.709-5”).

The processor 102 may be configured to select one or more multi-channelimage regions in the multi-channel image. In accordance with anembodiment, the one more multi-channel image regions may be selectedmanually, based on pixel coordinates provided by the user, via the I/Odevice 122. In accordance with an embodiment, the one more multi-channelimage regions may be selected automatically, based on a pattern and/oran image recognition technique, known in the art.

The selected one or more multi-channel image regions may comprise one ormore pixels of a pre-specified count. For example, a “5×5” multi-channelimage region comprises “25 pixels”. Each pixel from the one or morepixels in each region from the selected one or more multi-channel imageregions may be associated with one or more channels. In accordance withan embodiment, a count of channels of a color model may be based on acount of the one or more color channel components in each pixel from oneor more pixels in each region. For example, a count of color channels ineach pixel of the RGB color model is three. The three color channels areRed (R) channel, Blue (B) channel, or Green (G) channel. Thus, eachpixel in the RGB color model comprises three components, such as Redcomponent, Blue component, and Green component, each represented by an8-bit integer number with the value from 0 to 255. An integer numberwith different bits length (more or less bits than the 8-bit integernumber), or a floating number may also be used to record a pixel value.The processor 102 may communicate each region from the selected one ormore multi-channel image regions to the color adjustment unit 108 andthe demosaic unit 118.

In accordance with an embodiment, the color adjustment unit 108 may beconfigured to convert the multi-channel image, such as the RGB colorimage, into a mono-channel image. The one or more pixels in themono-channel image may be associated with limited pixel valueinformation. In other words, the one or more pixels in the mono-channelimage are not associated with color information, such as chrominance.The color adjustment unit 108 may be configured to adjust pixel valuesof one or more pixels in the multi-channel image region. The adjustmentof the pixel value associated with each pixel of the one or more pixelsin the multi-channel image region may be based on one or more factors,such as a difference between ambient viewing conditions and displayviewing conditions of the multi-channel image by the user.

In accordance with an embodiment, the adjustment of the pixel values maycorrespond to a white balancing operation on the pixel values of the oneor more pixels in the multi-channel image region. For example, the pixelvalues of the one or more pixels in the multi-channel image region in athree-channel component image may be adjusted, based on a mathematicaloperation expressed by equation (1), as follows:

$\begin{matrix}{\begin{bmatrix}R \\G \\B\end{bmatrix} = {\begin{bmatrix}{255/R_{w}^{\prime}} & 0 & 0 \\0 & {255/G_{w}^{\prime}} & 0 \\0 & 0 & {255/B_{w}^{\prime}}\end{bmatrix}\begin{bmatrix}R^{\prime} \\G^{\prime} \\B^{\prime}\end{bmatrix}}} & (1)\end{matrix}$where “255” and “0” correspond to white color and black color,respectively;“R”, “G” and “B” represents white balanced Red, Green, and Blue colorcomponents, respectively, of each pixel of one or more pixels in themulti-channel image region in the three-channel component image;“R′”, “G′”, and “B′” are the Red, Green, and Blue color components ofthe three-channel component image before white balancing; and“R′_(w)”, “G′_(w)”, and “B′_(w)” are the Red, Green, and Blue colorcomponents of a pixel, which may represent a white surface in thethree-channel component image before white balancing.

In accordance with an embodiment, the color adjustment unit 108 maycommunicate each region from the selected one or more multi-channelimage regions to the color modification unit 110, the PDD unit 112, andthe noise compensation unit 114. In accordance with an embodiment, thecolor modification unit 110, in conjunction with the processor 102, maybe configured to modify the pixel values of one or more pixels in theadjusted multi-channel image region. The modification may be based onone or more parameters, such as a pixel offset value and a pixel stepvalue, in accordance with a pre-specified signal pattern (such as apyramid pattern). In accordance with an embodiment, the pixel step valuemay be based on a center pixel value and an average of pixel values of aplurality of edge pixels at one or more edges of the adjustedmulti-channel image region. The pixel step value may be computed by thecolor modification unit 110 in conjunction with the processor 102, basedon a pixel step value function, as mathematically expressed as equation(3) in FIG. 2B.

In accordance with an embodiment, the pixel offset value may be based onan average of pixel values of a plurality of edge pixels at one or moreedges of the adjusted multi-channel image region and the pixel stepvalue. The pixel offset value may be computed by the color modificationunit 110 in conjunction with the processor 102, based on a pixel offsetvalue function, as mathematically expressed as equation (4) in FIG. 2B.In accordance with an embodiment, the color modification unit 110 maycommunicate the modified pixel values associated with one or more pixelsof each region from the one or more adjusted multi-channel image regionsto the PDD unit 112.

The PDD unit 112, in conjunction with the processor 102, may beconfigured to determine the pixel difference value between the adjustedpixel values and the modified pixel values of the one or more pixels ofeach multi-channel image region. As described above, the adjusted pixelvalues may be received from the color adjustment unit 108, and themodified pixel values may be received from the color modification unit110. The pixel difference values may be computed in accordance with oneof equations (5), (6), (7), or (8), as described in FIG. 2E.Notwithstanding, the disclosure may not be so limited and otherfunctions known in the art may also be utilized to compute the pixelvalue difference, without deviation from the scope of the disclosure.The PDD unit 112 may be further configured to communicate the pixeldifference value of each region to the scoring unit 116.

In accordance with an embodiment, the noise compensation unit 114, inconjunction with the processor 102, may be configured to determine athreshold noise level. The threshold noise level may correspond to theadjusted pixel values of the one or more pixels in the multi-channelimage region from the selected one or more multi-channel image regions.The noise compensation unit 114 may be further configured to perform anoise compensation operation on the adjusted pixel values of the one ormore pixels in the multi-channel image region to remove various types ofnoise signals. In accordance with an embodiment, the various types ofnoise signals may include, but are not limited to, a Gaussian noise, aSalt-and-pepper noise, a Shot noise, a Quantization noise (uniformnoise), a Film grain and/or an Anisotropic noise. The noise compensationunit 114 may be configured to communicate the threshold noise level tothe scoring unit 116.

In accordance with an embodiment, the scoring unit 116 may be configuredto receive the pixel difference value of each region from the PDD unit112 and the threshold noise level from the noise compensation unit 114.The scoring unit 116 may be further configured to determine a scorebased on a ratio of the pixel difference value and the maximum pixelstep value (that corresponds to the modified pixel values of one or morepixels in the multi-channel image region). The determined score maycorrespond to an indication of an extent to which the adjusted pixelvalues are similar to the modified pixel values.

In accordance with an embodiment, the scoring unit 116, in conjunctionwith the processor 102, may be further configured to perform acomparison between the determined score and a pre-determined threshold.In a particular instance, the score may be less than the pre-determinedthreshold. The instance corresponds to an absence of the pre-specifiedsignal pattern in the adjusted pixel values of the one or more pixels inthe multi-channel image region. Further, in a particular instance, thescore may exceed the pre-determined threshold. The instance correspondsto a presence of the pre-specified signal pattern in the adjusted pixelvalues of the one or more pixels in the multi-channel image region. Thescoring unit 116 may communicate the determined score to the FCS unit120.

In accordance with an embodiment, the demosaic unit 118, in conjunctionwith the processor 102, may be configured to receive the multi-channelimage that includes one or more multi-channel image regions. Thedemosaic unit 118, in conjunction with the processor 102, may beconfigured to perform interpolation on the received multi-channel imageto recover the full set of color channels from the multi-channel image.The interpolation may be performed pixel-by-pixel or block-by-block forevery region of the selected one or more multi-channel image regions ofthe received multi-channel image. In accordance with an embodiment, themulti-channel image may be received from a color filter array (CFA),such as Bayer filter, subsampled sensor data. In accordance with anembodiment, the demosaic unit 118 may introduce a color aliasing in thefull set of color channels of the one or more multi-channel imageregions, referred to as the color-aliased regions. The color aliasingmay comprise a spatial aliasing and/or a temporal aliasing techniqueknown in the art. The spatial aliasing may correspond to aspatially-sampled color channel and the temporal aliasing corresponds toa time-sampled color channel. The demosaic unit 118 may communicate therecovered full set of color channels of each multi-channel image regionfrom the selected one or more multi-channel image regions, to the FCSunit 120.

The FCS unit 120 may be configured to perform suppression of the falsecolor present in the recovered full set of color channels, based on thecomparison, the determined score, and the ratio of the pixel differencevalue and the maximum pixel step value. In accordance with anembodiment, the recovered full set of color channels with suppressedfalse color may correspond to a filtered set of color channels. The FCSunit 120 may utilize one or more image processing operations known inthe art, such as alpha blending, for such suppression. In accordancewith an embodiment, the alpha-blending operation may be expressedmathematically by equation (2), as follows:OUT_RB=(G−RB)*ratio+RB  (2)where “G” represents pixel value of the Green color channel from thefull set of color channels;“RB” represents pixel value of Red color channel and/or Blue colorchannel from the full set of color channels;“OUT_RB” represents pixel value of the Red color channel and/or the Bluecolor channel from the filtered set of color channels; and“ratio” represents a ratio that may be determined by the score generatedfrom the scoring unit 116.

FIG. 2A illustrates a first arrangement of various components of animage-processing device to determine a score, in accordance with anembodiment of the disclosure. The score may correspond to anidentification of a pre-specified signal pattern, such as the pyramidpattern, in adjusted pixel values of one or more pixels in amulti-channel image region. FIG. 2A is explained in conjunction withelements from FIG. 1. With reference to FIG. 2A, there is shown a firstarrangement 200 a of various components of the image-processing device100, such as the color adjustment unit 108, the color modification unit110, the PDD unit 112, the noise compensation unit 114, and the scoringunit 116, as described in FIG. 1. There is further shown a combination202 of a lens 202 a and a Bayer sensor 202 b in the data acquisitionunit 124. There is further shown a multi-channel image region 204 of amulti-channel image, an adjusted region 206, and a modified region 208.

In operation, the lens 202 a may focus light (reflected from an object(not shown)), on the Bayer sensor 202 b. The Bayer sensor 202 b maycapture at least one value per pixel location and each pixel value maycorrespond to red, green, or blue color channel information.Accordingly, the Bayer sensor 202 b may generate a multi-channel image,based on the captured pixel values. The multi-channel image may compriseone or more multi-channel image regions, such as the multi-channel imageregion 204. As shown in FIG. 2A, the multi-channel image region 204 maycomprise a pre-specified count of pixels, such as, “5×5 pixels”.Further, one or more pixels in the multi-channel image region 204 may beassociated with one or more color channels. For example, a first pixel204 a corresponds to Red color channel, a second pixel 204 b correspondsto Green color channel, and a third pixel 204 c corresponds to Bluecolor channel of the multi-channel image. The multi-channel image region204 may be communicated to the color adjustment unit 108.

The color adjustment unit 108 may be configured to adjust the pixelvalues of one or more pixels of the multi-channel image region 204. Thepixel values of the one or more pixels of the multi-channel image region204 may be adjusted by the color adjustment unit 108 based on the whitebalancing of the pixel values of the one or more pixels, as explained indetail in FIG. 1. The color adjustment unit 108 may be configured toconvert the multi-channel image region 204 to the adjusted region 206.The adjusted region 206 may be treated as a mono-channel image region.Thus, the adjusted pixel values of the one or more pixels in theadjusted region 206 are considered as grayscale values, although theseadjusted pixel values may represent information from Red color channel,Green color channel, or Blue color channel. The adjusted region 206 maybe communicated to the color modification unit 110, the PDD unit 112,and the noise compensation unit 114.

The color modification unit 110 may be configured to modify the pixelvalues of the one or more pixels in the adjusted region 206, based on apixel offset value and a pixel step value, in accordance with thepre-specified signal pattern, such as the pyramid pattern, which isknown in the art. The pixel step value and the pixel offset value isexplained in detail in FIG. 2B. In accordance with an embodiment, thecolor modification unit 110 may generate a modified region 208 whichcomprises one or more pixels with modified pixel values, as explained indetail in FIG. 2C. In accordance with an embodiment, the modified region208 may be communicated to the PDD unit 112.

The PDD unit 112 may be further configured to receive the adjustedregion 206 from the color adjustment unit 108 and the modified region208 from the color modification unit 110. The PDD unit 112 may determinea pixel difference value between adjusted pixel values of one or morepixels in the adjusted region 206 and modified pixel values of the oneor more pixels in the modified region 208. The pixel difference may bedetermined, based on various types of pixel difference functions thatmay refer to various mathematical functions. The various types of pixeldifference functions are explained in detail in FIG. 2E. The PDD unit112 may communicate the determined pixel difference value to the scoringunit 116.

Further, the noise compensation unit 114 may determine a threshold noiselevel of the adjusted pixel values of one or more pixels in the adjustedregion 206, received from the color adjustment unit 108. The noisecompensation unit 114 may be further configured to compensate varioustypes of noise signals associated with the adjusted pixel values of oneor more pixels in the adjusted region 206. The noise signals may becompensated based on one or more noise removal algorithms, such as alinear filtering, a median filtering, an adaptive filtering, and/or thelike. The noise compensation unit 114 may communicate the determinedthreshold noise level of the adjusted pixel values of one or more pixelsin the adjusted region 206, to the scoring unit 116.

The scoring unit 116 may be configured to receive the determined pixeldifference value from the PDD unit 112 and the determined thresholdnoise level from the noise compensation unit 114. The scoring unit 116may be configured to receive maximum pixel step value determined by thecolor modification unit 110. The maximum pixel step value corresponds tothe maximum pixel step value of the center pixel in the modified region208. For instance, when the maximum pixel step value exceeds thereceived threshold noise level for the adjusted region 206, the scoringunit 116 may determine a score based on a ratio of the pixel differencevalue and the maximum pixel step value.

The scoring unit 116, in conjunction with the processor 102, may befurther configured perform a comparison between the determined score andthe received threshold noise level. In an instance, when the score isless than the received threshold noise level, there may be nopre-specified signal pattern, such as the pyramid pattern, in theadjusted pixel values of the one or more pixels in the multi-channelimage region 204. In another instance, when the score exceeds thereceived threshold noise level, that may be a presence of thepre-specified signal pattern in the adjusted pixel values of the one ormore pixels in the multi-channel image region 204.

FIG. 2B illustrates a method for computation of a pixel step value and apixel offset value for a multi-channel image region, in accordance withan embodiment of the disclosure. FIG. 2B is explained in conjunctionwith elements from FIGS. 1 and 2A. With reference to FIG. 2B, there isshown an exemplary scenario 200 b that illustrates the adjusted region206. The adjusted region 206 comprises a plurality of edge pixels 206 aand a center pixel 206 b. The computed pixel step value may berepresented by “a”, and the pixel offset value may be represented by“d”.

In accordance with the exemplary scenario 200 b, the pixel step valuemay be computed by the color modification unit 110 in conjunction withthe processor 102, based on a pixel step value function. The pixel stepvalue function may be expressed mathematically by equation (3), asfollows:

$\begin{matrix}{a = \frac{\left( {C_{p} - {AE}_{p}} \right)}{3}} & (3)\end{matrix}$where “a” represents the pixel step value, “AE_(p)” represents anaverage pixel value of the plurality of edge pixels 206 a, and “C_(p)”represents the pixel value of the center pixel 206 b. In accordance withan embodiment, the pixel offset value may be computed based on a pixeloffset value function. The pixel offset value function may be expressedmathematically by equation (4), as follows:

$\begin{matrix}{d = \frac{\left( {{AE}_{p} - a} \right)}{3}} & (4)\end{matrix}$where “d” represents the pixel offset value, “AE_(p)” represents theaverage pixel value of the plurality of edge pixels 206 a, and “a”represents the pixel step value of the adjusted region 206.

FIG. 2C illustrates an exemplary scenario that represents acorrespondence between a modified region and a mathematicalrepresentation model of a 3D pyramid, in accordance with an embodimentof the disclosure. FIG. 2C is explained in conjunction with elementsfrom FIGS. 1 and 2A. With reference to FIG. 2C, there is shown anexemplary scenario 200 c that illustrates the adjusted region 206 and amathematical representation model 210. The mathematical representationmodel 210 corresponds to the modified region 208 generated by the colormodification unit 110. The mathematical representation model 210 may begenerated by the color modification unit 110 in conjunction with theprocessor 102, based on the pixel step value and the pixel offset value,computed based on the equations (3) and (4), respectively.

In accordance with the exemplary scenario 200 c, a first set of fourcorner pixels of the mathematical representation model 210 may becomputed, based on the pixel offset value, “d”. A second set of nexthorizontal and vertical adjacent pixels of the first set of pixels maybe computed, based on the combination, “d+a”, of the pixel offset value,“d”, and the pixel step value, “a”. Similarly, a third set of nexthorizontal and vertical adjacent pixels of the second set of pixels maybe computed, based on the combination, “d+2a”, of the pixel offsetvalue, “d”, and the next pixel step value, “2a”. Similarly, a fourth setof next horizontal and vertical adjacent pixels of the third set ofpixels may be computed, based on the combination, “d+3a”, of the pixeloffset value, “d”, and the next pixel step value, “3a”. Finally, thecenter pixel of the modified region 208 may be computed, based on thecombination, “d+4a”, of the pixel offset value, “d”, and the maximumpixel step value, “4a”.

FIG. 2D illustrates an exemplary scenario that represents a 3D pyramidmodel for a modified region, in accordance with an embodiment of thedisclosure. FIG. 2D is explained in conjunction with elements from FIGS.1, 2A, 2B, and 2C. With reference to FIG. 2D, there is shown anexemplary scenario 200 d that illustrates the modified region 208, themathematical representation model 210, and a corresponding 3D pyramidmodel 212.

With reference to the exemplary scenario 200 d, the color modificationunit 110 may be configured to generate the modified region 208, asillustrated in the mathematical representation model 210. For example,the pixel value of the center pixel 208 a in the modified region 208corresponds to the combination, “d+4a”, (depicted by 210 a) in themathematical representation model 210. Further, the pixel values of thefour corner pixels 208 b in the modified region 208 correspond to thepixel offset values, “d”, (depicted by 210 b) in the mathematicalrepresentation model 210. The pixel values of the one or more pixels inthe modified region 208 may be graphically represented by the 3D pyramidmodel 212. For example, the modified region 208 comprises the centerpixel 208 a and the corner pixels 208 b. The pixel value associated withthe center pixel 208 a corresponds to the peak 212 a of the 3D pyramidmodel 212. Further, pixel values associated with the corner pixels 208 bcorrespond to a minimum pixel value 212 b of the 3D pyramid model 212.Similarly, other pixel values associated with other pixels correspond tothe other values of the 3D pyramid model 212.

FIG. 2E illustrates an exemplary scenario that represents determinationof pixel difference values between adjusted pixel values and modifiedpixel values of one or more pixels of a multi-channel image region, inaccordance with an embodiment of the disclosure. FIG. 2E is explained inconjunction with elements from FIGS. 1 and 2A. With reference to FIG.2E, there is shown an exemplary scenario 200 e that illustrates the oneor more pixels in the adjusted region 206. Such one or more pixels inthe adjusted region 206 may be associated with adjusted pixel values.The exemplary scenario 200 d further illustrates the one or more pixelsin the modified region 208. Such one or more pixels in the adjustedregion 206 may be associated with modified pixel values. Thedetermination of the pixel difference value may be based on varioustypes of pixel difference functions, as explained below.

The PDD unit 112, in conjunction with the processor 102, may beconfigured to determine a pixel difference value between the adjustedpixel values and the modified pixel values of the one or more pixelsthat correspond to the multi-channel image region 204. The pixeldifference value may be computed in accordance with either of equations(5), (6), (7) or (8), or other such pixel difference function, known inthe art.

In accordance with an embodiment, the pixel difference value may becomputed mathematically by equation (5), as follows:PD_(SAD)(p,q)=Σ_(m,n) |p(m,n)−q(m,n)|  (5)where “PD_(SAD)(p,q)” may represent the pixel difference value based ona sum of absolute difference (SAD) function between the adjusted pixelvalues “p” and the modified pixel values “q”. Further, “m” may representa row value and “n” may represent a column value of the multi-channelimage region 204.

In accordance with an embodiment, the pixel difference value may becomputed mathematically by equation (6), as follows:PD_(SSD)(p,q)=Σ_(m,n) |p(m,n)−q(m,n)|²  (6)where “PD_(SSD)(p,q)” may represent the pixel difference value based onsum of squared difference (SSD) function between the adjusted pixelvalues “p” and the modified pixel values “q”. Further, “m” may representa row value and “n” may represent a column value of the multi-channelimage region 204.

In accordance with an embodiment, the pixel difference value may becomputed mathematically by equation (7), as follows:PD_(WSAD)(p,q)=Σ_(m,n) c(m,n)|p(m,n)−q(m,n)|  (7)where “PD_(WSAD)(p,q)” may represent the pixel difference value based onweighted sum of absolute difference (WSAD) function between the adjustedpixel values “p” and the modified pixel values “q”. Further, “c” mayrepresent a weighting factor for each pixel component, “m” may representa row value, and “n” may represent a column value of the multi-channelimage region 204.

In accordance with an embodiment, the pixel difference value may becomputed mathematically by equation (8), as follows:PD_(WSSD)(p,q)=Σ_(m,n) c(m,n)Σ_(m,n) |p(m,n)−q(m,n)|²  (8)where “PD_(WSSD)(p,q)” may represent the pixel difference value based onweighted sum of squared difference (WSSD) function between the adjustedpixel values “p” and the modified pixel values “q”. Further, “c” mayrepresent a weighting factor for each pixel component, “m” may representa row value, and “n” may represent a column value of the multi-channelimage region 204.

FIG. 3 illustrates a second arrangement of various components of animage-processing device, to depict a method and system for suppressionof color-aliased region of a demosaiced multi-channel image region of amulti-channel video frame, in accordance with an embodiment of thedisclosure. FIG. 3 is explained in conjunction with elements from FIGS.1 and 2A to 2E. With reference to FIG. 3, there is shown a secondarrangement 300 that depicts a method and system for suppression ofaliased colors in a multi-channel region 302 a of a multi-channel videoframe 302. There is further shown an adjusted region 306 and a modifiedregion 308, similar to the adjusted region 206 and a modified region208, respectively, shown in FIG. 2A. There is further shown anintermediate video frame 310, which corresponds to the multi-channelvideo frame 302. The intermediate video frame 310 may include amulti-channel image region 310 a, in which a pre-specified signalpattern, such as the pyramid pattern, is detected.

There is further shown a full set of color channels 312 that maycomprise one or more color channels, such as a first color channel 312a, a second color channel 312 b, and a third color channel 312 c,recovered by the demosaic unit 118 from the multi-channel region 302 a.There is further shown a reconstructed set of color channels 314, whichmay comprise a first reconstructed color channel 314 a, a secondreconstructed color channel 314 b, and a third reconstructed colorchannel 314 c. There is further shown a digitally reconstructedmulti-channel video frame 316, which includes a false-color suppressedframe region 316 a.

In operation, the combination 202 may focus light reflected from anobject (not shown) via the lens 202 a on the Bayer sensor 202 b. TheBayer sensor 202 b may capture at least one value per pixel location andeach pixel value may correspond to red, green, or blue color channelinformation. Accordingly, the Bayer sensor 202 b may generate amulti-channel video frame 302, based on the captured pixel values. Themulti-channel video frame 302 may comprise one or more multi-channelimage regions, such as the multi-channel region 302 a. As shown in FIG.3, the multi-channel region 302 a may comprise a pre-specified count ofpixels, such as, “5×5 pixels”, which may be represented by themulti-channel region 304, similar to the multi-channel image region 204as described in FIG. 2A. Further, one or more pixels in themulti-channel region 302 a may be associated with one or more colorchannels, such as Red color channel, Green color channel, and Blue colorchannel. The multi-channel region 304 that represents the multi-channelregion 302 a may be communicated to the color adjustment unit 108.

The color adjustment unit 108 may be configured to adjust the pixelvalues of one or more pixels of the multi-channel region 302 a. Thepixel values of the one or more pixels of the multi-channel region 302 amay be adjusted by the color adjustment unit 108 based on the whitebalancing of the pixel values of the one or more pixels, as explained indetail in FIG. 1. The color adjustment unit 108 may be configured toconvert the multi-channel region 302 a to the adjusted region 306. Theadjusted region 306 may be treated as a mono-channel image region. Thus,the adjusted pixel values of the one or more pixels in the adjustedregion 306 are considered as grayscale values, although these adjustedpixel values may represent information from Red color channel, Greencolor channel, or Blue color channel. The adjusted region 306 may becommunicated to the color modification unit 110, the PDD unit 112, andthe noise compensation unit 114.

The color modification unit 110 may be configured to modify the pixelvalues of the one or more pixels in the adjusted region 306, based on apixel offset value and a pixel step value, in accordance with thepre-specified signal pattern, such as the pyramid pattern, which isknown in the art. The computation of the pixel step value and the pixeloffset value is explained in detail in FIG. 2B. In accordance with anembodiment, the color modification unit 110 may generate a modifiedregion 308 which comprises one or more pixels with modified pixelvalues, as explained in detail in FIG. 2C. In accordance with anembodiment, the modified region 308 may be communicated to the PDD unit112.

The PDD unit 112 may be further configured to receive the adjustedregion 306 from the color adjustment unit 108 and the modified region308 from the color modification unit 110. The PDD unit 112 may determinea pixel difference value between adjusted pixel values of one or morepixels in the adjusted region 306 and modified pixel values of the oneor more pixels in the modified region 308. The pixel difference may bedetermined, based on various types of pixel difference functions thatmay refer to various mathematical functions. The various types of pixeldifference functions are explained in detail in FIG. 2E. The PDD unit112 may communicate the determined pixel difference value to the scoringunit 116.

Further, the noise compensation unit 114 may determine a threshold noiselevel of the adjusted pixel values of one or more pixels in the adjustedregion 306, received from the color adjustment unit 108. The noisecompensation unit 114 may be further configured to compensate varioustypes of noise signals associated with the adjusted pixel values of oneor more pixels in the adjusted region 306. The noise compensation unit114 may communicate the determined threshold noise level of the adjustedpixel values of one or more pixels in the adjusted region 306, to thescoring unit 116.

The scoring unit 116 may be configured to receive the determined pixeldifference value from the PDD unit 112 and the determined thresholdnoise level from the noise compensation unit 114. The scoring unit 116may be configured to receive maximum pixel step value, such as “4a”(FIG. 2C), determined by the color modification unit 110. The maximumpixel step value corresponds to the center pixel in the modified region308. For instance, when the maximum pixel step value exceeds thereceived threshold noise level for the adjusted region 306, the scoringunit 116 may determine a score based on a ratio of the pixel differencevalue and the maximum pixel step value.

The scoring unit 116, in conjunction with the processor 102, maydetermine a score for the multi-channel region 302 a. This method may bebased on a score that is determined (based on a ratio of the pixeldifference value and the maximum pixel step value), as described in thefirst arrangement 200 a of various components of the image-processingdevice 100. The pixel difference value may be received from the PDD unit112. The scoring unit 116, in conjunction with the processor 102, may befurther configured perform a comparison between the determined score andthe threshold noise level received from the noise compensation unit 114.For instance, when the score is less than the received threshold noiselevel, there may be no pre-specified signal pattern, such as the pyramidpattern, in the adjusted pixel values of the one or more pixels in themulti-channel region 302 a. In another instance, when the score exceedsthe received threshold noise level, that may be a presence of thepre-specified signal pattern in the adjusted pixel values of the one ormore pixels in the multi-channel region 302 a.

In accordance with an embodiment, the pixel values of the one or morepixels in the detected multi-channel image region 310 a may correspondto the 3D pyramid model 212, as explained in FIG. 2D. Thus, the presenceof the 3D pyramid model may be detected and depicted in themulti-channel image region 310 a, which is in the intermediate videoframe 310. The intermediate video frame 310 that includes the detectedmulti-channel image region 310 a may be communicated to the FCS unit120. The FCS unit 120 may further receive the full set of color channels312 of the multi-channel region 302 a from the demosaic unit 118. Thefull set of color channels 312 may be recovered by the demosaic unit118, based on one or more demosaic techniques known in the art. The fullset of color channels 312 may comprise the first color channel 312 a(such as the Red color channel), the second color channel 312 b (such asthe Green color channel), and the third color channel 312 c (such as theBlue color channel).

The FCS unit 120 may perform an alpha blending operation to suppressfalse color present in the full set of color channels 312 (received fromthe demosaic unit 118), based on the determined score (received from thescoring unit 116). The alpha blending operation may be performed inaccordance with the equation (2), as described in FIG. 1. Accordingly,the FCS unit 120 may generate the reconstructed set of color channels314. The reconstructed set of color channels 314 may comprise the firstreconstructed color channel 314 a (such as the reconstructed Red colorchannel), the second reconstructed color channel 314 b (such as thereconstructed Green color channel), and the third reconstructed colorchannel 314 c (such as the reconstructed Blue color channel). Thus, theFCS unit 120 may further generate the false-color suppressed frameregion 316 a, based on the reconstructed set of color channels 314.Accordingly, the digitally reconstructed multi-channel video frame 316may be generated, which may include the false-color suppressed frameregion 316 a.

FIG. 4 illustrates a flow chart for implementation of an exemplarymethod for processing a multi-channel image, in accordance with anembodiment of the disclosure. FIG. 4 is described in conjunction withelements of FIGS. 1, 2A to 2E, and 3. The method, in accordance with aflowchart 400 in FIG. 4, may be implemented in the image-processingdevice 100, as described in FIG. 1. With reference to FIG. 4, themethod, in accordance with the flowchart 400, begins at step 402 andproceeds to step 404.

At step 404, a multi-channel image, such as the multi-channel videoframe 302 (FIG. 3), captured by the data acquisition unit 124, may bereceived by the processor 102. The processor 102, in conjunction withthe data acquisition unit 124, may select a multi-channel image region,such as the multi-channel region 302 a, from one or more multi-channelimage regions in the multi-channel video frame 302.

At step 406, pixel values of the one or more pixels of the multi-channelregion 302 a may be adjusted by the color adjustment unit 108.Accordingly, the color adjustment unit 108 may determine the adjustedregion 306. The adjusted pixel values of the one or more pixels in theadjusted region 306 may comprise only pixel value information. Theadjusted pixel values of one or more pixels in the adjusted region 306may not comprise color information, such as chrominance.

At step 408, a pixel step value and a pixel offset value of the one ormore pixels in the selected the multi-channel image region 304 may becomputed by the color modification unit 110 in conjunction with theprocessor 102. At step 410, the adjusted pixel values of the one or morepixels in the multi-channel image region 304 may be modified, based onthe computed pixel step value and the pixel offset value, in accordancewith a pre-specified signal pattern. The modification may be performedby the color modification unit 110, to generate the modified region 308.

At step 412, a pixel difference value may be computed by the PDD unit112. The pixel difference value may be computed between the adjustedpixel values of the one or more pixels in the adjusted region 306, andthe modified pixel values of the one or more pixels in the modifiedregion 308. The pixel difference value may be computed, based on variouspixel difference functions that may include, but not limited to, the SADfunction, the SSD function, the WSAD function, and/or the WSSD, asdescribed in FIG. 2E. At step 414, a threshold noise level may bedetermined by the noise compensation unit 114. In accordance with anembodiment, compensation of noise may be performed on adjusted pixelvalues of one or more pixels in the adjusted region 306.

At step 416, a comparison may be performed between a maximum pixel stepvalue and the threshold noise level by the scoring unit 116. Inaccordance with an embodiment, the maximum pixel step value maycorrespond to the center pixel in the modified region 308. For instance,when the maximum pixel step value is less than the threshold noiselevel, the control passes to step 404. For instance, when the maximumpixel step value exceeds the threshold noise level, the control passesto step 418.

At step 418, the score may be determined by the scoring unit 116, basedon the ratio of the pixel difference value and the maximum pixel stepvalue. At step 420, a comparison between the determined score and apre-determined threshold may be performed by the scoring unit 116. In aninstance, when the score is less than the pre-determined threshold, thecontrol passes to step 404. Such an instance may correspond to anabsence of a 3D pyramid model in the adjusted pixel values of one ormore pixels in the adjusted region 306. In another instance, when thescore exceeds the pre-determined threshold, the control passes to step424. Such an instance may correspond to a presence of the 3D pyramidmodel in the adjusted pixel values of one or more pixels in the adjustedregion 306.

At step 422, a full set of color channels may be recovered by thedemosaic unit 118, from the multi-channel image region 304. At step 424,suppression of color difference may be performed for the full set ofcolor channels by the FCS unit 120 based on the ratio of the pixeldifference value and the maximum pixel step value. The FCS unit 120 maygenerate a set of reconstructed color channels, such as thereconstructed set of color channels 314. The FCS unit 120 may furthergenerate a false-color suppressed region, such as the false-colorsuppressed frame region 316 a, based on the reconstructed set of colorchannels 314. Accordingly, the digitally reconstructed multi-channelvideo frame 316 may be generated, which may include the false-colorsuppressed frame region 316 a. At step 426, it may be determined whetherthere are more multi-channel image regions in the multi-channel videoframe 302. In an instance, when there are more multi-channel imageregions, the control passes back to step 406. In an instance, when thereis no other multi-channel image region in the multi-channel video frame302, the control passes to end step 428.

In accordance with an embodiment of the disclosure, a system for imageprocessing may comprise the image-processing device 100 (as shown inFIG. 1). The image-processing device 100 may comprise one or moreprocessors, such as the processor 102, the color adjustment unit 108,the color modification unit 110, the PDD unit 112, the noisecompensation unit 114, the scoring unit 116, the demosaic unit 118, andthe FCS unit 120, as shown in FIG. 1. The color modification unit 110may be configured to modify adjusted pixel values of one or more pixelsin the region, such as the multi-channel region 302 a, of amulti-channel image, such as the multi-channel video frame 302, inaccordance with a pre-specified signal pattern, based on one or moreparameters. The scoring unit 116 may be configured to determine thescore based on the ratio of the pixel difference value and the maximumpixel step value. The maximum pixel step value may correspond to thecenter pixel when the maximum pixel step value exceeds a threshold noiselevel for the region. The FCS unit 120 may be configured to suppress thefalse color present in the multi-channel region 302 a and generate thefalse-color suppressed frame region 316 a.

Various embodiments of the disclosure may provide a non-transitorycomputer readable medium and/or storage medium, and/or a non-transitorymachine readable medium and/or storage medium with a machine code and ora computer program stored thereon, and with at least one code sectionexecutable by a machine and/or a computer for image processing. The atleast one code section in an image-processing device may cause themachine and/or computer to perform the steps, which may comprisemodification of adjusted pixel values of one or more pixels in amulti-channel image region, in accordance with a pre-specified signalpattern based on one or more parameters. Thereafter, based on a ratio ofa pixel difference value and a maximum pixel step value that correspondsto modified pixel values of one or more pixels in the multi-channelimage region, a score may be determined.

The present disclosure may be realized in hardware, or a combination ofhardware and software. The present disclosure may be realized in acentralized fashion, in at least one computer system, or in adistributed fashion, where different elements may be spread acrossseveral interconnected computer systems. A computer system or otherapparatus adapted to carry out the methods described herein may besuited. A combination of hardware and software may be a general-purposecomputer system with a computer program that, when loaded and executed,may control the computer system such that it carries out the methodsdescribed herein. The present disclosure may be realized in hardwarethat comprises a portion of an integrated circuit that also performsother functions.

The present disclosure may also be embedded in a computer programproduct, which comprises all the features enabling the implementation ofthe methods described herein, and which when loaded in a computer systemis able to carry out these methods. Computer program, in the presentcontext, means any expression, in any language, code or notation, of aset of instructions intended to cause a system having an informationprocessing capability to perform a particular function either directly,or after either or both of the following: a) conversion to anotherlanguage, code or notation; b) reproduction in a different materialform.

While the present disclosure has been described with reference tocertain embodiments, it will be understood by those skilled in the artthat various changes may be made and equivalents may be substitutedwithout departing from the scope of the present disclosure. In addition,many modifications may be made to adapt a particular situation ormaterial to the teachings of the present disclosure without departingfrom its scope. Therefore, it is intended that the present disclosurenot be limited to the particular embodiment disclosed, but that thepresent disclosure will include all embodiments falling within the scopeof the appended claims.

What is claimed is:
 1. An image-processing method, comprising: in animage-processing device: modifying, based on a first signal pattern,adjusted pixel values of at least one pixel in a region of amulti-channel image to generate modified pixel values; computing a pixeldifference value based on a difference between said adjusted pixelvalues and said modified pixel values of said at least one pixel in saidregion; determining, a score based on: a ratio of said pixel differencevalue and a maximum pixel step value that corresponds to said modifiedpixel values; and said maximum pixel step value that exceeds a thresholdnoise level for said region; and suppressing, false color in said regionof said multi-channel image, based on said score.
 2. Theimage-processing method of claim 1, wherein said maximum pixel stepvalue corresponds to a center pixel of said region, and wherein saidmaximum pixel step value is a maximum of said modified pixel values. 3.The image-processing method of claim 2, wherein said at least one pixelcomprises said center pixel and a plurality of edge pixels.
 4. Theimage-processing method of claim 3, wherein said plurality of edgepixels are at edges of said region.
 5. The image-processing method ofclaim 1, further comprising adjusting first pixel values of said atleast one pixel, based on white balancing of said first pixel values ofsaid at least one pixel.
 6. The image-processing method of claim 1,further comprising: modifying, said adjusted pixel values of said atleast one pixel, based on at least one parameter, wherein said at leastone parameter comprises a first pixel step value and a pixel offsetvalue.
 7. The image-processing method of claim 6, further comprisingcomputing, said first pixel step value, based on a center pixel valueand an average of second pixel values of a plurality of edge pixels atedges of said region.
 8. The image-processing method of claim 6, furthercomprising: computing, said pixel offset value based on an average ofsecond pixel values of a plurality of edge pixels at edges of saidregion and said first pixel step value, wherein said pixel offset valuecorresponds to a minimum pixel value from said modified pixel values ofsaid at least one pixel in said region.
 9. The image-processing methodof claim 1, further comprising computing, said pixel difference valuebased on at least one of a sum of absolute difference (SAD) function, asum of squared difference (SSD), a weighted sum of absolute difference(WSAD), or a weighted sum of squared difference (WSSD) function.
 10. Theimage-processing method of claim 1, further comprising compensatingnoise in said region based on said maximum pixel step value that is lessthan said threshold noise level for said region.
 11. Theimage-processing method of claim 1, further comprising identifying saidregion as a multi-channel image region with an arrangement of pixelvalues in a second signal pattern similar to said first signal pattern,based on said score.
 12. The image-processing method of claim 1, whereinfull set of color channels of said multi-channel image corresponds to ademosaiced multi-channel image.
 13. A multi-channel image processingsystem, comprising: memory configured to store instructions; and one ormore processors configured to execute the instructions stored in thememory, wherein the one or more processors are further configured to:modify, based on a first signal pattern, adjusted pixel values of atleast one pixel in a region of a multi-channel image to generatemodified pixel values; compute a pixel difference value based on adifference between said adjusted pixel values and said modified pixelvalues of said at least one pixel in said region; determine a scorebased on: a ratio of said pixel difference value and a maximum pixelstep value that corresponds to said modified pixel values; and saidmaximum pixel step value that exceeds a threshold noise level for saidregion; and suppress, false color in said region of said multi-channelimage, based on said score.
 14. The multi-channel image processingsystem of claim 13, wherein said maximum pixel step value corresponds toa center pixel of said region, and wherein said maximum pixel step valueis a maximum of said modified pixel values.
 15. The multi-channel imageprocessing system of claim 14, wherein said at least one pixel comprisessaid center pixel and a plurality of edge pixels.
 16. The multi-channelimage processing system of claim 15, wherein said plurality of edgepixels are at edges of said region.
 17. The multi-channel imageprocessing system of claim 13, wherein said one or more processors arefurther configured to adjust first pixel values of said at least onepixel, based on white balancing of said first pixel values of said atleast one pixel.
 18. The multi-channel image processing system of claim13, wherein said one or more processors are further configured tomodify, said adjusted pixel values of at least one pixel, based on atleast one parameter, wherein said at least one parameter comprises afirst pixel step value and a pixel offset value.
 19. The multi-channelimage processing system of claim 18, wherein said one or more processorsare further configured to compute said first pixel step value, based ona center pixel value and an average of second pixel values of aplurality of edge pixels at edges of said region.
 20. The multi-channelimage processing system of claim 18, wherein said one or more processorsare further configured to: compute said pixel offset value based on anaverage of second pixel values of a plurality of edge pixels at edges ofsaid region and said first pixel step value, wherein said pixel offsetvalue corresponds to a minimum pixel value from said modified pixelvalues of said at least one pixel in said region.
 21. The multi-channelimage processing system of claim 13, wherein said one or more processorsare further configured to compute said pixel difference value based onat least one of a sum of absolute difference (SAD) function, a sum ofsquared difference (SSD), a weighted sum of absolute difference (WSAD),or a weighted sum of squared difference (WSSD) function.
 22. Themulti-channel image processing system of claim 13, wherein said one ormore processors are further configured to compensate noise in saidregion based on said maximum pixel step value that is less than saidthreshold noise level for said region.
 23. The multi-channel imageprocessing system of claim 13, wherein said one or more processors arefurther configured to identify said region as a multi-channel imageregion with an arrangement of pixel values in a second signal patternsimilar to said first signal pattern, based on said score.
 24. Anon-transitory computer readable storage medium having stored thereon, aset of computer-executable instructions for causing a computer toexecute operations, the operations comprising: modifying, based on asignal pattern, adjusted pixel values of at least one pixel in a regionof a multi-channel image to generate modified pixel values; computing apixel difference value based on a difference between said adjusted pixelvalues and said modified pixel values of said at least one pixel in saidregion; determining, a score based on: a ratio of said pixel differencevalue and a maximum pixel step value that corresponds to said modifiedpixel values; and said maximum pixel step value that exceeds a thresholdnoise level for said region; and suppressing, false color in said regionof said multi-channel image, based on said score.